A study of geographical distance groups on length of visitors’ stay at local food festival destinations

Abstract

The primary aims of this study are to (1) explain the geographical distance groups (GDGs) in relation to the origin of visitors to local festival destinations, (2) examine the probability of visitors staying overnight at a festival destination as affected by GDGs and salient trip-related variables, and (3) identify the effects of GDGs and trip-related variables on length of stay (LOS). Data were collected during two local food festivals in the Midwestern area of the United States in 2010. The results of this study reveal that the consideration of geographical distance is most beneficial in capturing the target market for local festivals. Additionally, it is also found that LOS and overnight stay is predicted by the visitors’ trip-related characteristics of the destination, such as the number of previous visits to the festival, immediate group size, and distance from festival. From the results and findings of this study, managerial and academic implications are offered.

Keywords

Destination marketing geographical distance length of stay local food festivals overnight stay

Introduction

Research in the tourism industry has shown that successful destination marketing varies depending on the understanding of the viable target market by the destination management organizations (DMOs) (Guillet et al., 2011; Pan et al., 2008). One of the main goals of DMOs is to economically grow local destinations and identify tourism market trends for local tourism entities. A current challenge revealed in tourism research indicates that the spatial movement of tourists from origin to destination is a sensitive aspect on part of the tourist due to structural constraints (e.g. time, money, etc.) (Nyaupane and Andereck, 2008), in particular, to local festival destinations (Felsentein and Fleischer, 2003). This recent phenomenon indicates that people show a tendency to have more frequent short-term trips rather than fewer long-term trips in terms of both time and distance. In this regard, it is crucial to understand the primary visitors in a festival destination within the pattern of their geographical travel distance (Wixon, 2009). Given the fact that the majority of domestic tourists travel to destinations closer to home (Gray and Merritt, 2011) and visit a local destination for a special interest (i.e. food, music, crafts, etc.), these special interests should be considered in developing events (Papatheodorou et al., 2010).

Local theme events have been developed for several reasons such as celebrating holidays, promoting local cultural, facilitating economic impact, or providing educational experiences. Of these, local cultural and economic contributions have been the major objectives for implementing local festivals in many local communities (Mill and Morrison, 2010). For destinations that experience a lack of tourism activity and growth, local theme festivals have been used as a leverage tool to develop local tourism (Getz, 2008). Due to their positive impact on local economic growth, many local governments in the United States are becoming increasingly interested in attracting tourists to their festival destinations. Local theme festivals typically focus on one or a few special interest areas (e.g. food, wine, or local traditions) and create opportunities for individuals to take a trip. Of various types of festivals, food and wine festivals have been considered a motivating component in visitor’s intention to travel and willingness to travel departing from optimal distances (Park et al., 2008). The importance of local and regional food businesses has been identified as a way to increase local economy (Hingley et al., 2010) and should be considered by DMOs when developing events for destinations.

Substantial research has been devoted to identifying the contribution of hosting a local festival to destination, particularly examining visitors’ overnight stays (OSs) and length of stay (LOS) as the key elements in the understanding of sustainable destination development (Lee and Taylor, 2005; Saarinen, 2006; Tien et al., 2011). Among various types of local theme festivals in the United States, the food-related theme festival has increased in popularity and allows visitors to experience local products such as wine, organically produced products, and locally grown foods (Van Der Wagen and Carlos, 2005). Due to the popularity of food festivals as well as its positive impact on the development of local destinations (Hingley et al., 2010), DMOs have attempted to support these festivals for economic growth mainly targeting individuals near their communities. Therefore, identifying factors that lead to an increase in destination development is of considerable importance in local festival destinations.

Geographical distance in local festival context

Distance is defined as the scope from the visitor’s origin to the destination (Nicolau and Más, 2006). In destination marketing, distance has been regarded as a significant factor determining destination choice (McKercher et al., 2008). A considerable amount of tourism research has focused on the theory of distance decay that reveals a geographical insight in light of spatial relationships while examining the optimal range of distance from origin in terms of the mobility of international travelers (Eldridge and Jones, 1991; McKercher et al., 2008; McKercher and Lew, 2003). The theory of distance decay is addressed by previous tourism studies regarding the fact that tourism demand varies depending on whether travel distance increases or decreases. To support this issue, a number of studies examine (1) the relationship between visitors’ behavioral intentions and the distance from their origin and local festival areas (Liang et al., 2008), (2) the association between demand and visitors’ spatial movements from a source market to a tourism destination (McKercher et al., 2008; McKercher and Lew, 2003), and (3) the relation between travel distance and participating in leisure activities (Hinch et al, 2005). Thus, distance plays an important role in the distribution of ideas, technology, population, time, and spatial interactions on various types of tourism behaviors.

Recently, domestic tourists have attempted to minimize mobility costs using a private car, save lodging costs by staying overnight with a relative and/or family home, and comfortably enjoy local events (e.g. food and music festivals) as compared to vacation tourists that travel further distances (Sharma, 2009). The tourists’ responsive behaviors to the constraints of time and cost are normally observed when tourists are confronted with their mobility and localities from their home to a destination where they live (Kelkar, 2010). Gray and Merritt (2011) and Wixon (2009) propose that the features of domestic tourists pertains to traveling short distances (100 miles or less from origin to destination in one-way trip), visiting family and friends, and traveling to historical home sites, festivals, events, and activities near their communities. As described, current changes in travel patterns have been reflected in activities of the US travel market. Visitors are showing a trend of traveling closer to home and wanting money-saving values (UNWTO, 2010). In addition, these trip behaviors become more popular with the recent economic crisis in the United States. With the increase in individuals visiting friends and family, revisiting a destination, and destinations with a special interest (Papatheodorou et al., 2010), tourism activities such as visits to local facilities (e.g. parks and museums) and participation in local festivals are expected to have a more positive impact on local economic growth. Given the current tourism trend of tourists, local DMOs should focus on capturing the attention of potential domestic visitors within a radius that maximizes the revenue brought to a destination.

Determinants of visitor’s stay in local festivals

In a tourism destination, focusing on overnight tourists is of considerable importance in the sense that they are larger monetary spenders than day-trip visitors (Leones et al., 1998). For this reason, overnight tourists are considered the target market to increase tourism revenue in comparison with day-trip tourists at a destination (Scheyvens, 2007). Given this fact, tourists who stay overnight at a destination tend to spend more money due to the extension of their trip duration by enjoying tourism activities (Kim et al., 2008; Kozak, 2004). This tendency indicates that the decision to extend the trip duration yields more expenditures in the categories of visitors’ activities and consumptions with regard to visiting more tourism attractions (Scheyvens, 2007) as well as food and beverage, shopping, transportation, and purchasing locally produced foods in tourism and/or local festivals (Cela et al., 2007; Kim et al., 2008).

It has been posited that the overall impact of tourists in a given economy depends on LOS, which increases expenditures (Gokovalia et al., 2007; Menezes et al., 2008). Attendees who are visitors to a destination have been observed to have a higher “willingness to pay” than those attendees that are classified as local and are more likely to contribute to a higher economic impact (Herrero et al., 2012). With the recognition of the significant economic impact of LOS (and OS) on destinations, there is a need for research that examines the determinants of increasing the likelihood of OS and predictors of increasing LOS in local festival destinations.

In this regard, it is assumed that the probability of OS is closely related to geographical distance groups (GDGs) and individuals’ trip-related characteristics. Among the salient factors of OS, distance is regarded as one of the most important variables in destination marketing. As stated, the theory of distance decay is proof of the importance of distance and examines the optimal range of distance from origin in regard to mobility of international travelers (McKercher et al., 2008; McKercher and Lew, 2003). Additionally, the effect of distance has been utilized in the destination choice model (Fesenmaier, 1988; Nicolau and Más, 2006). The effect of distance model indicates that the individual’s decision-making process is influenced by distance when determining a destination to visit. With the understanding of the findings, it is postulated that geographical distance is a salient predictor of determining visitors’ travel duration for event participation at a local destination. Visitors might stay longer or shorter dependent on origin distance to destination. Therefore, there would be an optimal range of geographical distance to attract more potential visitors to local events from DMOs’ perspectives.

Individual differences of tourists have been found to result in positive effects in regards to distance from the festival destination (Nicolau, 2008). For example, a positive effect would be observed for those tourists that travel within an optimal range and such as regional visitors that maximizes the total amount of cumulative dollars spent at the destination. The intention to stay overnight might increase the amount of cumulative dollars spent within a destination and therefore have a greater positive impact on the destination. Thus, the increase in overnight visitors who are from local and/or regional areas is more beneficial than the same day visitors.

Furthermore, significant determinants of LOS in a tourism destination are individual characteristics including age, trip budget, trip party size, friends at a destination, and trip experience (Barrosa and Correia, 2007; De Menezes and Moniz, 2011). A significant amount of studies have also examined other influential factors in relation to LOS such as occupation, repeat visitation rate, price as travel motive, total holiday expenditure (Alegre and Pou, 2006; Gokovalia et al., 2007; Nicolau, 2008), and trip purpose (Barros et al., 2010). Additionally, visitors’ likelihood to revisit a festival destination or festival increases when their emotional attachment to the destination is positive and overall experience is positive (Lee et al., 2012).

Therefore, DMOs should make efforts that enhance visitors’ emotional ties not only to a destination but also to a festival as well to increase the likelihood of repeat visitors. Locals or those attendees who are not geographically distant from the festival destination tend to have a greater appreciation for the cultural contributions of festivals (Herrero et al., 2012) and could be viewed as a contributing factor of emotional ties to a destination. Consequently, visitors’ trip-related variables can be regarded as determinants of increasing the probability of visitors’ OS and/or LOS at local festival destinations.

Aims of this study

A substantial amount of studies posited that OS and LOS varied according to geographical distance from visitors’ origin to destinations and individual trip-related characteristics (Barros et al., 2010; Gokovalia et al., 2007; Nicolau, 2008; Nicolau and Más, 2006). Despite this fact, there is a paucity of research that identifies target visitors by adapting geographical groups within an optimal range of distance. It is assumed that local festival visitors would be from a certain range of distance in different distance groups and trip characteristics, therefore making it possible for local festival destinations to identify certain geographical groups as well as their trip-related characteristics. Hence, LOS that directly increases visitors’ expenditure at a destination should be examined in a better understanding of trip characteristics of tourists, while considering the visitor’s GDGs in local food festivals. The primary aims of this study are to (1) explain the GDGs in relation to the origin of visitors to the festival destinations, (2) examine the probability of visitors staying overnight at a festival destination affected by GDGs and salient trip-related variables, and (3) identify the effects of GDGs and trip-related variables on LOS.

Methods

To reach the proposed objectives of this study, this study collected information about visitors’ trip-related characteristics utilizing a questionnaire. The questionnaire was distributed in two local food festivals held in a Midwestern county in the United States. This is an appropriate setting because it meets the following criteria: (1) the festivals should be held in local areas when considering the objective of this study that focuses on local food promotion, (2) the target market should be individual and/or group attendees from out of market in a food-related event participation (indicating a large number of out-of-market visitors), and (3) the transportation of the festival attendees from origin to destination should be by car.

Target sample

Surveys were conducted by asking randomly selected festival attendees for their voluntary participation. Random selection was developed by survey collectors that would intercept visitors in various locations within the festival site while not targeting any particular demographic (i.e. race, gender, age, group size, etc.). Visitors were identified by asking their county and zip code. If an attendee had a zip code within the hosting county where the festival was held, they were thanked for their time and the survey was not conducted. However, if the visitor indicated a zip code outside of the hosting county, the visitor was then asked to complete the survey. A total of 631 festival attendees were intercepted, indicating 418 in festival A and 213 in festival B, respectively (see Table 1). A valid survey is deemed by those attendees that live outside of the festival county and volunteered to complete the survey; a total of 184 respondents (127 in food festival A (FFA) and 57 in food festival B (FFB)) were valid in this study. The remainder 447 questionnaires were not deemed valid because they were event attendees that lived within the city limits of the festival destination and not considered a visitor.

Table 1.

Procedure of valid sample selection.

Procedure	FFA (n)	FFB (n)	Remark	Total (n)
Total attendees intercepted	418	213	Random selection	631
Visitors from the hosting county	291	156	Local residents	447
Target samples intercepted	127	57	Initial target sample	184
Data screening	12	6	Above 3.29 SD	18
Valid sample	115	51	Target sample	166

FFA: food festival A; FFB: food festival B.

Note: The valid sample only includes out-of-market visitors who does not reside at a hosting county.

Survey instrument

The random selection of visitors to the two local food festivals (FFA and FFB) was conducted during the period from May to June 2010 to empirically explore the influence of visitor’s trip characteristics toward OS at the two festivals. Based on the instrument derived from previous studies regarding trip characteristics influencing visitors’ OS and LOS at a destination, the survey instrument included questions on visitors’ trip-related characteristics such as OS, LOS, the number of previous visits to the festival (NVF), primary travel purpose for the festival (PTP), immediate group size (IG), the number of persons from a hosting county (NPHC), zip code (GOG), and total budget (TB) were included in the questionnaire.

This study defines the variables used and identifies the dependent and independent variables. As dependent variables, OS is asked as the dummy variable of yes (=1) and no (=0) for logistic regression. LOS is asked of respondents as an open-ended question and is also coded as the three categories such as “1 day (=1),” “2 day (=2),” and “over 3 day (=3)” for the χ ² test. Independent variables for the two empirical tests are as follows: (1) NVF is collected with a dummy variable that utilizes a value of 1 if a respondent is a first-time visitor and 0 if he/she is a repeat visitor to the festival, (2) PTP is found with a dummy variable, where 1 indicates that a respondent considers this aspect when visiting the festival and 0 if not, (3) IG refers to by the following categorical variables: one person; immediate group 1, two persons; immediate group 2, three persons; immediate group 3, and more than four persons; immediate group 4, (4) NPHC is coded as a dummy variable that takes a value of 1 if an immediate group includes at least one person who is a resident at a hosting area and 0 if a resident is not accompanied with immediate group, and (5) GOG refers to geographical travel distance from visitors’ origin to festival destination in a shortcut (McKercher, 2008), calculated using the Google maps.

Data screening

For the utilization of the data set in empirical analyses, a data screening for missing values was first conducted. Missing values were checked by frequency analysis; as a result, there were many missing values in TB on retail, revealing that the item should not be utilized in this study. In the second procedure, the outliers were deleted based on criterion of 3.29 SD above/below the mean. It was found that the z-scores of distance ranged from −0.567 to 6.427, indicating that there were outliers in the distance item. Thus, 18 outliers were deleted from the data set. Of the initial sample of 184 individuals (or groups), the total sample size that was usable was 166.

Data analysis

To achieve the objectives of this study, an empirical analysis was conducted as follows. First, the frequency analysis was conducted to identify the respondents’ characteristics. Second, the difference between trip-related characteristics and LOS within the target festival area was identified in an application of a χ ² analysis. Third, multiple regression analysis was used to identify the effects of GDGs with trip-related variables on length of visitor’s stay. Finally, logistic regression analysis was conducted to examine the probability of OS influenced by respondents’ GDGs and trip-related characteristics.

Results

Respondent characteristics

As indicated in Table 2, the respondent characteristics are as follows. The majority of the respondents stayed overnight (61.4%) and was their first time to attend the festival (81.3%). Of the respondents that stayed overnight, 51.2% stayed an average of 2 days. In regards to the primary purpose of travel to Columbia, Missouri, 83.1% indicated that attending the festival was their primary purpose. The most predominant IG was two people at 49.4%. While the majority of respondents indicated that they had traveled between 101 and 150 miles (36.7%) from the destination, closely behind this was respondents that had traveled between 51 and 100 miles (30.7%).

Table 2.

Respondent’s trip-related characteristics (n = 166).

Variables		Frequency (n)	Ratio (%)
Overnight stay	Yes	102	61.4
	No	64	38.6
Length of stay (mean = 1.7 days)	1 day	66	39.8
	2 days	85	51.2
	3 or 4 days	15	9.0
Number of visit to the festival	First-time visit	135	81.3
Number of visit to the festival	Repeat visit	31	18.7
Primary travel reason for the festival	Yes	138	83.1
Primary travel reason for the festival	No	28	16.9
Number of persons from a hosting county	Yes	41	24.7
	No	125	75.3
Immediate group	1 person	30	18.1
	2 person	82	49.4
	3 person	29	17.5
	More than 4 person	25	15.1
Geographical distance groupst^a	D1	40	24.1
	D2	51	30.7
	D3	61	36.7
	D4	14	8.4

^aD1 = less than 50 miles, D2 = 51–100 miles, and D3 = 101–150 miles, and D4 = more than 151 miles in the distance range of GDGs from minimum (20.7 miles) to maximum (249 miles).

Results of the χ ² analysis

The χ ² analysis was conducted to identify the differences between the five predictor variables used by the logistic regression analysis to examine the probability of OS and the three categories of the LOS (see Table 3). As anticipated, NVF, IG, and distance, χ ² = 13.849, p < 0.01, χ ² = 24.120, p < 0.05, and χ ² = 16.035, p < 0.01, respectively, were statistically significant. More specifically, the LOS category of 1 day (92.4%) related to the first-time visit to the festival and was slightly more than the categories of 2 days (77.6%) and over 3 days (67.9%). Significant results also indicated that there were a relatively high proportion of visitors with two accompanied persons in the immediate group, LOS 1 (43.9%) and LOS 2 (55.3%) except for the category of more than four persons (40.0%) in LOS 3. In terms of the distance variable, it was found that about 42% of LOS 1 revealed a slightly higher proportion in the D1 as compared to other distance groups (i.e. D2, D3, and D4), while there was a relatively high proportion of visitors with D3 in both LOS 2 and LOS 3.

Table 3.

LOS by the visitor’s trip-related variables in the local food festivals (N = 166).

		LOS, N (%)^a
Variables		LOS 1	LOS 2	LOS 3	χ ²
NVF	First time	61 (92.4)	66 (77.6)	8 (53.3)	13.849**
NVF	Repeat time	5 (7.6)	19 (22.4)	7 (46.7)	13.849**
PTP	Yes	57 (86.4)	71 (83.5)	10 (66.7)	3.401
PTP	No	9 (13.6)	14 (16.5)	5 (33.3)	3.401
NPHC	Yes	49 (74.2)	68 (80.0)	8 (53.3)	4.941
NPHC	No	17 (25.8)	17 (20.0)	7 (46.7)	4.941
IG	1	18 (27.3)	12 (14.1)	–	24.120*
	2	29 (43.9)	47 (55.3)	6 (40.0)
	3	13 (19.7)	13 (15.3)	3 (20.0)
	≥4	6 (9.1)	13 (15.3)	6 (40.0)
Distance	D1	28 (42.4)	11 (12.9)	1 (6.7)	16.035**
	D2	18 (27.3)	28 (32.9)	5 (33.3)
	D3	19 (28.8)	35 (41.2)	7 (46.7)
	D4	1 (1.5)	11 (12.9)	2 (13.3)

LOS: length of stay; NVF: number of previous visits to the festival; PTP: primary travel purpose for the festival; NPHC: number of persons from a hosting county; IG: immediate group size.

Note: LOS 1 = 1 day, LOS 2 = 2 days, and LOS 3 = 3 or 4 days.

*p < 0.05, **p < 0. 01.

Geographical approach in local food festival promotion

Figure 1 indicates the range of distance between visitors’ origin and the festival destination. The observed average distance range was 92.62 miles (SD = 46.53) from origin to festival destination (n = 166), minimum = 20.70 miles, and maximum = 249.00 miles. Given the z-score of each distance group, the probability was calculated as seen in Figure 1. The equation was specified as

Z = \frac{x_{i (D_{1} {, D}_{2}, D_{3}, D_{4})} - μ_{(D_{1} {, D}_{2}, D_{3}, D_{4})}}{σ_{(D_{1} {, D}_{2}, D_{3}, D_{4})}}, r e s p e c t i v e l y .

As a result, it was found that the z-score of distance groups was −1.21 (D1), −0.32 (D2), 0.56 (D3), and −1.40 (D4), respectively. In this respect, it appears that the primary range of GDGs in local food festivals would be from D2 (37.4%) to D3 (28.8%). This shows that destination management organization (DMOs) could designate the range of GDGs as mainstream areas within a geographical promotional approach.

Determinants of OS and LOS

This study conducted two empirical analyses to identify whether trip-related variables have effects on visitors’ OS and LOS in using logistic regression analysis and multiple regression analysis, respectively.

At first glance, the variable of OS was dichotomized into OS (yes = 1) and non-OS (no = 0) and regressed on the factors in model 3 in a logistic fashion (see Table 4). The result of omnibus tests of model coefficients indicated that the model with predictors is significantly different from the constant-only model, χ ²(9) = 41.492, p < 0.001. In other words, this result shows that the model with predictors is a statistically significant improvement over the constant-only model. According to the Nagelkerke R ², about 30% of variance is explained by the model with predictors. In this study, furthermore, the overall percentage correctly predicted is 73.5%. Specifically, in the group of the OS, 85.3% is correctly predicted and in the group of OS, 73.5% is correctly predicted. Compared to the overall percentage correctly predicted in the constant-only model (61.4%), there is an improvement in the model to successfully predict OS in the festival area with three predictors.

Table 4.

The probability for being classified as group of overnight stay.

Variable	B (SE)	Wald	Exp. (B)	95% Confidence interval for Exp. (B)
Variable	B (SE)	Wald	Exp. (B)	Lower	Upper
Distance (reference = D1)
D2	1.99 (.51)	15.47	7.33**	2.72	19.78
D3	1.73 (.49)	12.59	5.66**	2.17	14.73
D4	2.65 (.88)	9.08	14.10**	2.52	78.87
IG (reference = 1 person)
2 person	1.01 (.50)	4.16	2.74*	1.04	7.23
3 person	0.76 (.60)	1.58	2.13	0.66	6.95
>4 person	1.50 (.74)	4.15	4.49**	1.06	19.04
NVF (reference = First time)	1.56 (.60)	6.79	4.74**	1.47	15.29
PTP (reference = No)	−0.19 (.51)	0.15	0.82	0.30	2.23
NPHC (reference = No)	−0.74 (.46)	2.54	0.48	0.19	1.19
(Constant)	−3.18 (.14)	8.67	0.04
Model fit	χ² (sig.): 41.492(.000); −2 Log likelihood: 179.856; % correct: 73.5%; and Nagelkerke R ²: .30

IG: immediate group size; NPHC: number of persons from a hosting county; PTP: primary travel purpose for the festival; NVF: number of previous visits to the festival.

*p < 0.05; **p < 0.01.

Table 4 shows significance of each predictor. According to logistic regression analysis, each variable, that is, NVF (p < 0.01), IG (p < 0.05), and distance (p < 0.01), is a significant predictor of visitors’ OS in a festival area. Specifically, the likelihood of OS increases by about 4.7 times when a respondent is a repeat visitor to the festival. The probability to stay overnight at the festival destination area increases by about 2.7 times and about 4.5 times as one person and three persons added to the immediate group, respectively. Finally, the likelihood of staying overnight at the festival hosting area increases by about 7.3 times, about 5.7 times, and about 14.1 times when a visitor is from the distance range of 51–100 miles, 101–150 miles, and more than 151 miles, respectively, in the distance range of geographical groups within the context of local food festivals. In sum, distance groups IG (two and more than four person) and repeat time group increase the likelihood of being an overnight tourists. Finally, it appears that visitors from the range of GDGs (D2, D3, and D4), repeat time visitors, and couple or family visitors, as opposed to their respective reference categories, would be more likely to stay overnight.

To shed some additional insight on the factors determining the visitors’ LOS while at the local festival destination, three steps of multiple regressions were employed to examine the effects of distance and other trip-related variables on LOS. In model 1 in Table 5, LOS is regressed on the distance variable only; in model 2, the group variable was included because target population was group visitors within the range of certain geographical realm and theoretically informed the prominent explanatory factor of GDGs (dummy: D2, D3, and D4) previously discussed are added to model 1, and in model 3, the remaining factors are added to model 2.

Table 5.

Effects on length of stay: multiple regression results.

Variable	Model 1		Model 2		Model 3
Variable	β (SE)	t value	β (SE)	t value	β (SE)	t value
Distance (DUM)
D2	0.46 (0.14)	3.25**	0.43 (0.14)	3.11**	0.48 (0.13)	3.58**
D3	0.51 (0.14)	3.75**	0.45 (0.13)	3.31**	0.37 (0.13)	2.82**
D4	0.75 (0.21)	3.59**	0.63 (0.21)	3.03**	0.62 (0.20)	3.10**
IG (DUM)
2 person			0.27 (0.14)	1.94*	0.28 (0.14)	2.09*
3 person			0.23 (0.17)	1.36	0.30 (0.17)	1.79
>4 person			0.60 (0.18)	3.33**	0.51 (0.18)	2.75**
NVF ((DUM) = 1)					0.49 (0.18)	3.63**
PTP ((DUM) = 1)					0.27 (0.18)	2.03*
NPHC (DUM = 1)					−0.06 (0.18)	−0.51
(Constant)	1.33 (0.11)		1.10 (0.14)		0.23 (0.26)
Adjusted R ²	0.09		0.14		0.21
R ² change			0.06		0.08
F value for change in R ²			5.37		5.80
p value for change in R ²			<0.01		<0.01

IG: immediate group size; NPHC: number of persons from a hosting county; PTP: primary travel purpose for the festival; NVF: number of previous visits to the festival.

Note: DUM: (dummy) variables were coded as “1.”

*p < 0.05; **p < 0.01.

Three steps of multiple regression analysis were used to examine the effects of distance variable and other salient variables on LOS. As a result, the explained variance according to model 1 is slightly small, while model 1 is appropriately significant (F value = 6.69; df = 3; p < 0.01), revealing that other factors should be added to model 1 when predicting LOS in a more accurate manner. In model 2 (Table 5), three dummy variables of IG are added to the regression equation. Model 2 shows the expected increase in explanatory power compared to model 1 (ΔR ² change: 06). In addition, IG1 and IG3 have positive impacts on LOS. In model 3, the remaining factors are added to the regression equation. Model 3 also indicates the expected increase in explanatory power compared to model 2 (ΔR ² change: 08). In more detail, the results of model 3 in Table 5 suggest that distance, IG (only two and more than four persons), NVF, and PTP have significant and positive impacts on LOS except for PTP. These results indicate that visitors who are from the origin of D2 (β = 0.48), D3 (β = 0.37), and D4 (β = 0.62), group visitors including two person (β = 0.28) or more than four person (β = .30), first-time visitors (β = .49), and visitors who have the primary purpose of visiting the festival destination may stay longer than the opposite reference variable, respectively. Additionally, attendees who are accompanied by relatives or friends that live within the festival destination county are less likely to stay longer at the festival destination within the context of local food festivals.

Discussion

Considering the current economic situation in the United States, DMOs should focus on examining new marketing strategies to develop and increase the local economy. A significant tool for local economic growth is developing and hosting local festivals, which leads to visitors’ expenditure in a destination. However, the limited tourism budget makes it necessary for DMOs to recognize their primary target markets within the optimal range of their spatial area. For empirical analyses, data were collected through a questionnaire conducted in two local food festivals in a Midwestern county of the United States in 2010. The results of this study revealed the GDGs (i.e. from D2 to D4) are most beneficial in resulting in OSs. The results also indicated that the probability of visitor’s OS varies depending on respondents’ trip-related characteristics.

Given the previously mentioned results, the current study offers a unique insight into the relationship between visitors’ travel distance and LOS. The research result shows that visitors who live close to local festival areas (D2) tend to stay longer than visitors who live relatively away from festival host areas (D3) as compared to D2. This is inconsistent with previous studies that address that visitors may stay longer to make up for the increased travel distance (cost) at a destination area (Wang et al., 2012). The different finding may occur due to the fact that visitors who live closer to festival host areas may stay with their family and/or friends within the festival destination. Other aspects of research findings are consistent with previous studies that suggest that LOS at a festival destination varies relying on visitors’ trip-related characteristics, including NVF, number of IG, and distance from origin to festival destination (Alegre and Pou, 2006; Barros et al., 2010; Gokovalia et al., 2007; Nicolau, 2008; Nicolau and Más, 2006). Moreover, the results indicated that there were statistically significant differences between the categories of LOS and the salient trip-related variables. Consequently, the trip-related variables (e.g. IG, NVF, and PTP) should be considered when determining LOS with the distance variable with the context of local festival.

Conclusions

From the discussed findings and results, there are several recommendations raised by this research. First, DMOs need to consider the geographical distance to promote their festivals. In general, the promotional costs are divided into two components: fixed cost (e.g. website operation) and variable cost (e.g. printed materials: brochure, flyers, etc.). For a local festival promotion, it seems that one of the ways to overcome the limited promotional budget would be to minimize the variable cost for their promotion. This indicates that DMOs need to consider the most beneficial distance to disseminate the printed promotional materials.

In this study, the optimal range of travel distance was about 50–200 miles from origin to festival destination, presenting strong opportunities for collaborative promotional marketing among DMOs within festival hosting regions identified in the range of travel distance between 50 and 200 miles. That is, each regional DMO needs to share annual festival schedules to effectively promote their local festivals for potential visitors. For instance, sharing banner ads about festivals on Web sites among regional DMOs could be a collaborative promotion strategy for the identified distance. Thus, it seems that DMOs can efficiently allocate the minimal budget for the potential target markets in the optimal range of geographical distance (e.g. about 50–200 miles from festival hosting areas). As a result, DMOs can minimize the promotional cost in their oriented theme festivals (e.g. food festivals).

The results of this study also showed that the individuals’ trip-related variables including first-time and group (family) visitors are significant determinants for increasing the likelihood of visitors’ OS at a local festival destination. Given the finding that those who include more than two people in a group are more likely to stay overnight and stay longer than other groups at the festival destination, DMOs need to provide a beneficial discount for group visitors (e.g. for family and/or couple ticket) at the festival destination. The finding also revealed that the first-time visitors were the primary target population for local food festivals (about 81%). Compared to repeat visitors, first-time visitors tend to visit friends/family and typically participate in a variety of event activities and indicate that offering discount or promotional items for the first-time visitors is important (e.g. for family tickets and/or event activities) (Lau and McKercher, 2004; Li et al., 2008).

Given the significant respondents’ travel pattern mentioned above, furthermore, this study suggests the following characteristics of tourists that are more likely to stay overnight when attending a local food festival when they (a) travel distances ranging about 50–200 miles from origin to destination (one-way trip), (b) travel to festivals, events, and activities (as a primary purpose), (c) are group (family) visitors, (d) visit and stay with their family and/or friends, and (e) attend other family friendly activities in neighboring counties and towns. These characteristics of local destination tourists are similarly associated with an emerging concept of a “staycation,” which can be defined as an individual or family that stays and relaxes at home, or vacations in a certain range of distance and takes trips to area attractions close to home (Gray and Merritt, 2011). It has been also noted that staycation tourists can minimize mobility costs using a private car, cut lodging costs by staying with a relative and/or family home, and comfortably enjoy local events (e.g. food and music festivals) as compared to vacation tourists that travel further distances (Sharma, 2009). The recognition of an emerging styaycation concept makes it possible for future studies to identify the characteristics of staycation travelers in comparison with traditional domestic tourists within the context of local destinations.

Consequently, the understanding of the travel distance and visitors’ trip-related variables should be crucial for DMOs to determine their marketing strategies in developing their local businesses such as a food market through the local festivals. This effort might result in an increase in local economic growth. Thus, it would be of potential value for each DMO within the United States to have a deeper insight into the variables that shape the decisions and actions of local niche festival visitors in each destination, such as distance from the destination. Additionally, the results of this study are relevant not only to DMOs but also to field of research related to food tourism in regards to recruitment of attendees and realization of attendees travel characteristics. Therefore, food tourism should focus on festival attendees in a realization of the target market and the appropriate channel choice (i.e. local publications, billboards, social media, etc.) to increase visibility of marketing and in return result in ticket purchase to the festival.

Recommendations for future research

This study has few limitations. First of all, this study only focused on the food-related theme festivals at a local destination. For this limitation, it should be necessary for each DMO to identify the various types of local theme festivals (i.e. music, performance, etc.) in segmenting their specific target characteristics for each theme festival. Second, the sampling was restricted to a single destination, and one should be cautious in generalizing the conclusions and implications because the sample was drawn exclusively from visitors to a specific festival destination in the Midwest. In order to draw more generalized conclusions, a larger data set involving multiple local festivals in varying destinations would be necessary, but the heterogeneity issue would presumably still remain. Finally, the significant demographic and individual variables such as gender, income, occupation, and so on were not included in this study. This was because the purpose of this study was to intercept the out-of-market attendees who were individual or group visitors, indicating that a respondent in the group of visitors cannot be a representative for the demographic information of each member.

Footnotes

Acknowledgement

The authors would like to thank Julie Ausmus (Tourism Development Program Manager of Columbia CVB, MO) and Amy Schneider (Director of Columbia CVB, MO). Without their support this research could not have been developed. Additionally, the authors would like to thank the City of Columbia for supporting the grant that enables us to conduct a series of survey collections used in this research

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

References

Alegre

Pou

(2006) The length of stay in the demand for tourism. Tourism Management 27(6): 1343–1355.

Barros

Butler

Correia

(2010) The length of stay of golf tourism: a survival analysis. Tourism Management 31(1): 13–21.

Barrosa

Correia

(2007) Survival Analysis in Tourism Demand: The Length of Stay in Latin American Destinations, Working papers. Portugal: University of the Algarve.

Cela

Knowles-Lankford

Lankford

(2007) Local food festivals in Northeast Iowa communities: a visitor and economic impact study. Managing Leisure 12 (2–3): 171–186.

De Menezes

Moniz

(2011) Determinants of length of stay: a parametric survival analysis. Tourism Analysis 16(5): 509–524.

Eldridge

Jones

(1991). Warped space: a geography of distance decay. Professional Geographer 43(4): 500–511.

Felsentein

Fleischer

(2003) Local festivals and tourism promotion: the role of public assistance and visitor expenditure. Journal of Travel Research 41(4): 385–392.

Fesenmaier

(1988) Integrating activity patterns into destination choice models. Journal of Leisure Research 20(3): 175–191.

Getz

(2008) Event tourism: definition, evolution, and research. Tourism Management 29 ( 3 ): 403–428.

10.

Gokovalia

Bahara

Kozakb

(2007) Determinants of length of stay: a practical use of survival analysis. Tourism Management 28(3): 736–746.

11.

Gray

Merritt

(2011) The Everything Family Guide to Budget Travel: Hundreds of Fun Family Vacations to Fit Any Budget. Avon, MA: Adams Media Inc.

12.

Guillet

Lee

Law

Leung

(2011) Factors affecting outbound tourists’ destination choice: the case of Hong Kong. Journal of Travel and Tourism Research 28(5): 556–566.

13.

Herrero

Sanz JA Bedate

Barrio

(2012) Who pays more for a cultural festival, tourists or locals? A certainty analysis of a contingent valuation application. International Journal of Tourism Research 14(5): 495–512.

14.

Hinch

Jackson EL Hudson

Walker

(2005) Leisure constraint theory and sport tourism. Sport in Society 8(2): 142–163.

15.

Hingley

Boone

Lindgreen

(2010) Development of local and regional food networks: Cases from the UK. In: 26th IMP-conference, Budapest, Hungary, September 2010, pp. 1-21. Available at: http://impgroup.org/uploads/papers/7478.pdf accessed 1 September 2012.

16.

Kelkar

(2010) The great American staycation and the risk of stillness summertime fun: staycations, big trips and sending kids off examiner staff writer. Available at: http://www.sfexaminer.com/local/Summertime-fun-Staycations-big-trips-and-sending-kids-off-94600299.html. (Accessed 10 September 2012).

17.

Kim

Han

Chone

(2008) Estimation of the determinants of expenditures by festival visitors. Tourism Analysis 13(4): 387–400.

18.

Kozak

(2004) Destination Benchmarking: Concepts, Practices and Operations. Oxon, UK: CAB International.

19.

Lau

McKercher

(2004) Exploration versus Acquisition: A comparison of first-time and repeat visitors. Journal of Travel Research 42(3): 279–285.

20.

Lee

Taylor

(2005) Critical reflections on the economic impact assessment of a mega-event: the case of 2002 FIFA world cup. Tourism Management 26(4): 595–603.

21.

Lee

Kyle

Scott

(2012) The mediating effect of place attachment on the relationship between festival satisfaction and loyalty to the festival hosting destination. Journal of Travel Research 51(6): 754–767.

22.

Leones

Colby

Crandall

(1998) Tracking expenditures of the elusive nature tourists of Southeastern Arizona. Journal of Travel Research 36(3): 56–64.

23.

Chengb CK Kimc

Petrick

(2008) A systematic comparison of first-time and repeat visitors via a two-phase online survey. Tourism Management 29(2): 278–293.

24.

Liang

Illum

Cole

(2008) Benefits received and behavioural intentions of festival visitors in relation to distance travelled and their origins. International Journal of Event Management Research 4(1): 12–23.

25.

McKercher

(2008) The implicit effect of distance on tourist behavior: a comparison of short and long haul pleasure tourists to Hong Kong. Journal of Travel and Tourism Marketing 25 ( 3 ): 367–381.

26.

McKercher

Lew

(2003) Distance decay and the impact of effective tourism exclusion zones on international travel flows. Journal of Travel Research 42(2): 159–165.

27.

McKercher

Chan

Lam

(2008) The impact of distance on international tourist movements. Journal of Travel Research 47(2): 208–224.

28.

Menezes

Moniz

Vieira

(2008) The determinants of length of stay of tourists in the Azores. Tourism Economics 14(1): 205–222.

29.

Mill

Morrison

(2010) The Tourism System. 6th ed. Dubuque, IA, USA: Kendall Hunt Publishing Co.

30.

Nicolau

(2008) Characterizing tourist sensitivity to distance. Journal of Travel Research 47(1): 43–52.

31.

Nicolau

MásFJ (2006) The influence of distance and prices on the choice of tourist destinations: the moderating role of motivations. Tourism Management 27(5): 982–996.

32.

Nyaupane

Andereck

(2008) Understanding travel constraints: application and extension of a leisure constraints model. Journal of Travel Research 46(4): 433–439.

33.

Pan

Chon

Song

(2008) Visualizing tourism trends: a combination of ATLAS.ti and BiPlot. Journal of Travel Research 46(3): 339–348.

34.

Papatheodorou

Rosello

Xiao

(2010) Global economic crisis and tourism: consequences and perspectives. Journal of Travel Research 49(1): 39–45.

35.

Park

Reisinger

Kang

(2008) Visitors' motivation for attending the south beach wine and food festival, Miami beach, Florida. Journal of Travel and Tourism Marketing 25(2): 161–181.

36.

Saarinen

(2006). Traditions of sustainability in tourism studies. Annals of Tourism Research 33: 1121–1140.

37.

Scheyvens

(2007) Poor cousins no more: valuing the development potential of domestic and diaspora tourism. Progress in Development Studies 7(4): 307–325.

38.

Sharma

(2009) The great American staycation and the risk of stillness. M/C Journal 12(1) Available at: http://journal.media-culture.org.au/index.php/mcjournal/article/viewArticle/122 (Accessed 10 September 2012).

39.

Tien

Lim

(2011) The economic benefits of mega events: a myth or a reality? A longitudinal study on the Olympic Games. Journal of Sport Management 25(1): 11–23.

40.

The World Tourism Organization (UNWTO) (2010) ITB world travel trends report 2010/2011. Available at: https://s3-eu-west1.amazonaws.com/storageapi/sites/all/files/pdf/itb_world_travel_trends_report_2010_-_2011.pdf (Accessed 10 September 2012).

41.

Van Der Wagen

Carlos

(2005) Event Management for Tourism, Cultural, Business, and Sporting Events. Upper Saddle River, NJ: Prentice Hall.

42.

Wang

Little

DelHomme-Little

(2012) Factors contributing to tourists' length of stay in Dalian northeastern China: a survival model analysis. Tourism Management Perspectives 4: 67–72.

43.

Wixon

(2009) The Great American Staycation: How to Make a Vacation at Home Fun for the Whole Family (and Your Wallet!). Avon, MA: Adams Media.

A study of geographical distance groups on length of visitors’ stay at local food festival destinations

Abstract

Keywords

Introduction

Geographical distance in local festival context

Determinants of visitor’s stay in local festivals

Aims of this study

Methods

Target sample

Survey instrument

Data screening

Data analysis

Results

Respondent characteristics

Results of the χ 2 analysis

Geographical approach in local food festival promotion

Determinants of OS and LOS

Discussion

Conclusions

Recommendations for future research

Footnotes

Acknowledgement

Funding

References

Results of the χ ² analysis